M. Khalid Ijaz | Environmental Science | Visionary Research Award

M. Khalid Ijaz | Environmental Science | Visionary Research Award

Dr M. Khalid Ijaz, Reckitt, United States

Dr. M. Khalid Ijaz is a distinguished virologist and immunologist specializing in aerovirology, infectious diseases, and microbiology. With decades of expertise, he has made groundbreaking contributions to understanding airborne viral transmission, bioaerosols, and antimicrobial technologies. He has held leadership roles in renowned organizations like Reckitt Benckiser and Clorox, pioneering research in air decontamination and respiratory virus survival. His extensive publication record, including studies on coronavirus, rhinoviruses, and biofilms, highlights his impactful scientific contributions. Honored with prestigious awards like the 2024 R&D 100 Award, his innovative research continues to shape global public health policies.

Publication Profile

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Education

Dr. M. Khalid Ijaz is a distinguished microbiologist and immunologist with a strong academic foundation in veterinary and medical sciences. He earned his Doctor of Veterinary Medicine (DVM) in 1976 and an MSc (Honors) in Microbiology in 1979 from the University of Agriculture, Pakistan. He became a Registered Microbiologist (RM) in Microbiology, Virology, and Immunology from the Canadian College of Microbiologists in 1984. He obtained his PhD in Microbiology & Immunology (Virology) from the University of Ottawa, School of Medicine, in 1985. He further honed his expertise with a Post-Doctorate Fellowship in Immunobiology/Vaccinology at the University of Saskatchewan, VIDO, in 1987. 🎓🧪🏅

Experience

With a distinguished career in scientific research and product development, he has been serving as the Director of Scientific Affairs at Reckitt Benckiser since 2020 🌍. Prior to this role, he was a Senior Research Fellow (2018-2020) 🔬 and a Research Fellow (2007-2018) at the same company, contributing to groundbreaking innovations. His expertise extends to his tenure as Research Manager at Clorox Services Company (2005-2007) 🧴, where he played a key role in product safety and efficacy. Earlier, he held leadership positions at Microbiotest, Inc., serving as Vice President and Director (1998-2005), driving advancements in microbiological testing 🏭.

Awards and Honors

Renowned for groundbreaking contributions, this distinguished researcher earned the prestigious 2024 R&D 100 Award 🏅, often called the “Oscars of Innovation.” Their journey of excellence began with the Medical Research Council Fellowship Award 🎖️ in 1987, recognizing outstanding scientific achievements. In 1982, they received the WHO Research Trainee Award 🌍, highlighting their impact on global health research. That same year, their academic promise was acknowledged with the Graduate Student Entrance Scholarship 🏛️. Their early dedication to excellence was evident in 1976 when they received a Certificate of Merit 🎖️, marking the start of an illustrious career in research and innovation.

Presentation

Dr. M. Khalid Ijaz actively contributed to the 18th ISAIQ INDOOR AIR 2024 in Honolulu, Hawaii 🌴, exploring virus aerosolization and resuspension 🦠💨. As a co-chair, he led discussions on airborne virus dynamics. His research covered toilet flushing and cleaning effects on viral contamination 🚽🔬, the efficacy of air sanitizers in reducing airborne pathogens 🌬️🛡️, and virus dispersal from floor surfaces during indoor activities 🏠🦠. Collaborating with renowned scientists, Dr. Ijaz’s work enhances understanding of airborne disease transmission and effective mitigation strategies, crucial for public health and indoor air quality 🌎🏥.

Research Focus

Aerovirology explores the airborne transmission of viruses, focusing on aerosolization and resuspension. 💨🦠 This field examines how viruses travel through the air, their stability, and potential risks to public health. Infectious diseases research delves into microbiology, virology, and immunology, uncovering mechanisms of disease spread and immune responses. 🏥🧬 Understanding pathogens at a microscopic level aids in developing treatments and preventive strategies. Microbiology further extends to antimicrobial technologies, biofilms, and microbiological techniques, enhancing infection control and medical advancements. 🧫🔬 These interconnected fields contribute to safeguarding public health by improving detection, prevention, and management of infectious agents.

Publication Top Notes

  1. “Survival characteristics of airborne human coronavirus 229E” 🦠 (1985)
  2. “The global war against intestinal parasites—should we use a holistic approach?” 🤢 (2010)
  3. “An outbreak of Crimean-Congo hemorrhagic fever in the United Arab Emirates, 1994-1995” 🌎 (1997)
  4. “Assessment of a respiratory face mask for capturing air pollutants and pathogens including human influenza and rhinoviruses” 🎭 (2018)
  5. “Spread of viral infections by aerosols” 💨 (1987)
  6. “Generic aspects of the airborne spread of human pathogens indoors and emerging air decontamination technologies” 🌆 (2016)
  7. “Effect of relative humidity on the airborne survival of rhinovirus-14” 💧 (1985)

 

Masoud Mahdianpari | Environmental Science | Research Hypothesis Excellence Award

Masoud Mahdianpari | Environmental Science | Research Hypothesis Excellence Award

Dr Masoud Mahdianpari, Memorial University of Newfoundland/C-CORE, Canada

Based on the provided information, Dr. Masoud Mahdianpari is indeed a strong candidate for the Research for Research Hypothesis Excellence Award. His extensive educational background, professional experience, and contributions to the field of remote sensing and data science highlight his qualifications.

Publication profile

google scholar

Educational Background

Dr. Masoud Mahdianpari holds a Ph.D. in Electrical Engineering from Memorial University of Newfoundland (2015-2019), along with a Master’s in Remote Sensing Engineering and a Bachelor’s in Geomatics Engineering, both from the University of Tehran (2010-2013, 2006-2010). His robust academic foundation has equipped him with advanced knowledge in remote sensing and data analysis.

Professional Experience

Currently serving as a Cross-appointed Professor at Memorial University of Newfoundland and Remote Sensing Technical Lead at C-CORE, Ottawa, Dr. Mahdianpari has significant experience in applying machine learning and remote sensing technologies. His previous roles include Remote Sensing Scientist and Research Assistant at C-CORE, where he has developed expertise in image processing, feature extraction, and target detection.

Research Expertise

Dr. Mahdianpari specializes in machine learning, big data technologies, and radar remote sensing. His work encompasses high-resolution image processing, environmental monitoring, and GHG emission estimation. He is leading several projects focused on wetland mapping and methane emission estimation in the Arctic, leveraging advanced remote sensing data and cloud computing platforms.

Professional Appointments

As an associate editor for various journals, including IEEE Geoscience and Remote Sensing Letters and Frontiers in Environmental Science, Dr. Mahdianpari contributes to the academic community and promotes high-quality research. He is a member of several professional societies, such as IEEE and ASPRS, demonstrating his active engagement in the field.

Recent Honors and Awards

Dr. Mahdianpari has been recognized for his contributions to science, including being ranked in the top 1% of scientists worldwide (2023-2024) and receiving multiple awards for his research excellence. Notably, he has secured grants such as the NSERC Discovery Grant (2022-2027) and the Microsoft AI for Earth grant, highlighting his innovative work in environmental monitoring.

Project Leadership

Dr. Mahdianpari is currently leading the ESA Carbon Science Cluster project, aiming to enhance methane emission estimates from wetlands in the Arctic. This project underscores his leadership in addressing critical environmental challenges and advancing remote sensing methodologies.

Research Interests

His research focuses on environmental monitoring and wetland mapping using remote sensing data, emphasizing machine learning and multi-sensor image classification. Currently, he leads projects related to greenhouse gas (GHG) monitoring, showcasing his commitment to addressing pressing environmental issues.

Project Experience

He currently leads a project for the European Space Agency focused on improving methane emission estimates from wetlands, an initiative of significant environmental importance. This role emphasizes his leadership in research that impacts global environmental policies.

Publications and Presentations

Dr. Mahdianpari has authored numerous influential publications, including studies on remote sensing image classification and advanced machine learning applications in environmental monitoring. His research has contributed significantly to the field, evidenced by his citations and presentations at major international conferences.

Conference Contributions

He has presented at several prestigious conferences, showcasing his research on water quality monitoring and electrical potential preservation. His publications in leading journals further establish his reputation as a thought leader in remote sensing and environmental science.

Conclusion

In summary, Dr. Masoud Mahdianpari’s outstanding qualifications, research contributions, and recognition in the field make him a highly suitable candidate for the Research for Research Hypothesis Excellence Award. His dedication to advancing remote sensing technology and addressing pressing environmental issues through innovative research exemplifies excellence in academic and applied research.

Publication top notes

Google Earth Engine for geo-big data applications: A meta-analysis and systematic review

Support vector machine versus random forest for remote sensing image classification: A meta-analysis and systematic review

Very deep convolutional neural networks for complex land cover mapping using multispectral remote sensing imagery

Random forest wetland classification using ALOS-2 L-band, RADARSAT-2 C-band, and TerraSAR-X imagery

The first wetland inventory map of newfoundland at a spatial resolution of 10 m using sentinel-1 and sentinel-2 data on the google earth engine cloud computing platform

Deep convolutional neural network for complex wetland classification using optical remote sensing imagery

A new fully convolutional neural network for semantic segmentation of polarimetric SAR imagery in complex land cover ecosystem

Comparing deep learning and shallow learning for large-scale wetland classification in Alberta, Canada

A systematic review of landsat data for change detection applications: 50 years of monitoring the earth

Bagging and boosting ensemble classifiers for classification of multispectral, hyperspectral and PolSAR data: a comparative evaluation